Our proposed pipeline consists of two parts: 1. A unified neural network architecture with ResNet-20 [1]}, [2]} and the NetVLAD layer [3]}, and 2. A re-ranking strategy to improve final results. The first part itself consists of three main steps (depicted in Figure REF ): The ResNet-20 with the NetVLAD layer to extract local image descriptors and their corresponding embeddings, An orderless aggregation function to pool obtained embeddings of each image into one global image descriptor, and the normalization and PCA [4]} dimensionality reduction of resulted global image descriptors.
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